With the increasing popularity of Internet enabled mobile devices, and a plethora of mobile web applications in use, the data consumption on smartphones has sky-rocketed over the past years. Many carriers have reported a staggering increase in mobile data traffic. While the flat rate plans in countries including the US tend to come with a maximum data limit, users across the globe continue to be enrolled in usage-based plans.
Wi-Fi based wireless mesh networks present a high bandwidth, and often cheaper, alternative to mobile Internet users, and a good option for service providers to offload the mobile data traffic. For satisfactory user experience, mobile Internet applications such as the delay sensitive Voice-over-IP, warrant seamless connectivity in areas with wireless coverage. However, this is taxing on the mobile phone battery owing to reconnections needed because of user mobility, and short transmission range of Wi-Fi networks. Specifically, to maximize the usage of Wi-Fi opportunities, mobile hosts have to (i) frequently scan ISM spectrum bands to obtain a list of available Wi-Fi networks, (ii) actively probe the wireless links to identify the best access network or access point (AP), and (iii) proactively migrate their current association to other APs that provide high throughput. All of these tasks are critical to both battery lifetime and connectivity of mobile hosts.
There are several inherent challenges in maximizing the utility of Wi-Fi usage for battery constrained mobile clients. Periodic scanning of Wi-Fi networks can help identify available networks. It is challenging to determine optimal scanning frequency to optimize battery lifetime and Wi-Fi connectivity opportunities. Cellular-assisted distance-based scanning provided by existing cellular service providers suffers from unpredictability of cellular signals or varying density of cell towers. Some existing devices utilizes received signal strength (RSS) based scanning, which relies on to a fixed threshold in triggering AP scanning, is not flexible enough to take advantage of diverse Wi-Fi access opportunities offered by the wireless mesh networks. Still some exiting devices utilize history-based scanning and association control, which require energy-intensive computations and location tracking.
In a wireless mesh network (WMN), a mobile client is able to hear from multiple APs belonging to the network and selects one of the APs to access the WMN. It is therefore desired to select an AP that provides the mobile client with optimal user experience or performance. Existing systems primarily utilize a signal strength based mechanism for ranking APs, where a mobile client is associated with the AP that provides the maximum received signal strength (RSS) at the client.
However, selecting APs merely on the basis of signal strength can cause increased congestion at the selected APs, thereby resulting in poor performance for the end users. Moreover, signal strength is not an accurate indicator of channel conditions in a wireless network. Therefore, even if the received signal strength from an AP is high, it may not correctly indicate the current performance level of that AP.